Climate Control System Research Articles

Sliding Mode Control Based on Disturbance Observer for Greenhouse Climate Systems

Greenhouses are closed environments that require careful climatic control, which can benefit from a system control method to cope with the high nonlinearity, complex coupling, and robustness of unknown disturbances. This paper presents a general framework for an integral sliding mode controller based on a disturbance observer combined with feedback linearization for a greenhouse temperature and humidity system. The first-principle greenhouse climate model is described as a standard affine nonlinear system. The feedback linearization control law is used to achieve a system consisting of two separate integrator channels for temperature and humidity. System compound disturbances are estimated by applying a sliding mode disturbance observer. Based on the observer, an integral sliding mode control is incorporated to enhance the robustness against uncertainties and guarantee satisfactory tracking performance even when there are unknown estimation errors. The validity and efficacy of the proposed control technique for greenhouse climate tracking were verified by comparison with simulation results obtained using the common sliding mode control method using feedback linearization without the disturbance observer. Based on this comparison, the developed controller shows a faster system response speed, higher control precision, and stronger anti-interference ability. This method can be applied to improve greenhouse climate control systems.

Simulator with integrated HW and SW for prediction of thermal comfort to provide feedback to the climate control system

The aim of the paper is to assemble a simulator for evaluation of thermal comfort in car cabins in order to give a feedback to the HVAC (heating, ventilation and air conditioning) system. The HW (hardware) part of simulator is formed by thermal manikin Newton and RH (relative humidity), velocity and temperature probes. The SW (software) part consists of the Thermal Comfort Analyser (using ISO 14505-2) and Virtual Testing Stand of Car Cabin defining the heat loads of car cabin. Simulator can provide recommendation for the climate control how to improve thermal comfort in cabin by distribution and directing of air flow, and also by amount of ventilation power to keep optimal temperature inside a cabin. The methods of evaluation of thermal comfort were verified by tests with 10 test subjects for summer (summer clothing, ambient air temperature 30 °C, HVAC setup: +24 °C auto) and winter conditions (winter clothing, ambient air temperature -5 °C, HVAC setup: +18 °C auto). The tests confirmed the validity of the thermal comfort evaluation using the thermal manikin and ISO 14505-2.

Analysis and Experimental Investigation of Optimum Design of Thermoelectric Cooling/Heating System for Car Seat Climate Control (CSCC)

The optimum design of a thermoelectric system for application in car seat climate control has been modeled and its performance evaluated experimentally. The optimum design of the thermoelectric device combining two heat exchangers was obtained by using a newly developed optimization method based on the dimensional technique. Based on the analytical optimum design results, commercial thermoelectric cooler and heat sinks were selected to design and construct the climate control heat pump. This work focuses on testing the system performance in both cooling and heating modes to ensure accurate analytical modeling. Although the analytical performance was calculated using the simple ideal thermoelectric equations with effective thermoelectric material properties, it showed very good agreement with experiment for most operating conditions.

This fabric can give you your own personal climate-control system

This fabric can give you your own personal climate-control system

MATHEMATICAL MODEL OF THE BIOTECHNIC SYSTEM CONTROLLED BY THE SYSTEM OF ANIMAL SYSTEM ON THE EXAMPLE OF INFRARED IRRADIATION OF PIG-REMOVAL

This article proposes a model biotechnical system and exposure control algorithm on the behavior of piglets using machine vision technology. The effective temperature of the indoor air is an indirect indicator of the favourable conditions for keeping animals. In this article, a hypothesis has been put forward: the management of the microclimate in the cattle-breeding premises should be based on direct indicators of the favourableness of the content. This indicator is appropriate to consider the behaviour of animals. Structurally functional schemes for the functioning of the biotechnical system of the cattle-breeding complex have been developed in the IDEF0 notation. An algorithm for controlling the irradiation of piglets and weaners based on the ethological character of the location of animals across the floor area is presented. This problem was not solved before. Algorithms for automatic control of electro technological processes in agriculture have not been encountered in the literature before. The developed principle of intelligent control allows optimal provision of comfortable conditions for keeping animals in real time. The results can be used to create and design of modern automatic climate control systems in livestock.

Experimental Research of Drying Red Chili by Two Methods: Solar Drying and Low - Temperature System Drying

The objective of this research was to experiment of solar drying and Low-Temperature system drying (45-50%RH, 27-30°C) for drying red chili. Solar drying during daytime (greenhouse dryer) and during at night using climate control system to coordinate with air conditioner in drying. The Low-Temperature system consists the humidity control unit (ultrasonic), air-conditioner, temperature and relative humidity sensor, heating coil and microcontroller unit. For Low-Temperature drying process, climate control system controls the compressor in the air conditioner by turn on-off to control the temperature and relative humidity in the chamber. The dehumidification process by controlling the temperature of the surface evaporator coil is decreased to the dew point temperature, making water vapor in the air condensed to be water drops. The result of solar drying and Low-Temperature system takes 52h to reduce the moisture content of about 74% to 13.5% (w.b). For temperature and relative humidity of the solar drying at 50 °C and 36%RH by average, in during daylight and at night with Low-temperature drying system by the climate control system coordinate with air conditioning system in moisture reduction at 27-30°C and relative humidity at 45-50%RH for drying chili in the night. These processes were found to have average temperatures and relative humidity for drying at 27.55°C, 47.37% RH., moisture condensation rate and specific energy consumption at 2.16 kgwater/h and 0.75 MJ/kg.

Design of a smart system for indoor climate control in historic underground built environment

The application of sensors-actuators networks in Building Heritage can lead to significant improvement in indoor climate control, with the aim to both reduce energy consumption, and improve conditions for occupants and hosted Heritage. This study proposes the preliminary design of a smart indoor climate control system, based on low-impact application criteria, which can be applied to visited underground built environment. The system is based on the balance of hygrothermal loads. Sensors and actuators requirements are defined, and control algorithm are based on the comparison between real-time monitored and “natural” temperature and hygrometric values (for stationary and transitory conditions).

Differential response of plant species to greenhouse microclimate created by design technology and ambient conditions

Food insecurity amongst First Nation populations living on reserves across Canada is purported to be about 27% of the national average. However, crop production is limited by factors such as climate and soil conditions. A 2-yr study was carried out to assess production of collard (Brassica oleracea L. var. acephala DC. ‘Champion’), carrot (Daucus carota L. ‘Adelaide’), and tomato (Lycopersicon esculentum Mill. ‘Beefsteak’) in three separate greenhouses with contrasting design technologies. The greenhouses were categorized as (i) high technology (HTG), (ii) medium technology (MTG), and (iii) low technology (LTG) greenhouses. The MTG and LTG were basic facilities but the MTG had in-floor heating. The HTG was fully equipped with climate control systems. Mean monthly air temperature was stable at 23 °C ± 1 °C in the HTG but fluctuated in the MTG and LTG. Air temperature and water loss were highest in the MTG. Vapour pressure deficit and daily light integral followed the trends LTG > MTG > HTG > ambient and am...

An experimental investigation of dehumidifying and reheating performances of a dual-evaporator heat pump system in electrified vehicles

Climate control system in electrified vehicle is quite different from traditional internal combustion engine vehicle, as it cannot use the wasted coolant heat from engine to keep warm of the cabin. For the dehumidifying and reheating air in the electrified vehicle cabin, the use of a dual-evaporator heat pump system could improve the total energy utilization efficiency of the climate control system. In this study, an experimental dual-evaporator heat pump system was set up to investigate dehumidifying and reheating efficiency of a cabin in electrified vehicle. Two dehumidifying modes were chosen in this experiment. One was single-evaporator mode with indoor evaporator only, and the other was dual-evaporator mode with both indoor and outdoor evaporators. The dual-evaporator dehumidifying mode shows higher heat capacity, coefficient of performance, and outlet air temperature, while it has quite lower moisture extraction rate and specific moisture extraction rate compared to the single-evaporator dehumidifying mode. Therefore, a hybrid dehumidifying and reheating method was suggested as a possible option for realization of energy conservation without sacrifice of thermal comfort for passengers.

On human–machine relations

This paper presents an approach to human---machine interactions based on the concept of teamwork and the psychological theory of object relations. We envision the human and the machine in a close relationship that has many aspects of human-to-human relations. Not only does the machine have to relate to and accommodate human wants and needs, but also, to some extent, the human is called to reciprocate. We propose a framework consisting of eleven attributes that describe generic processes in teamwork: commitment, goal definition, common ground, belief, planning, transparency, sensitivity, caring, responsibility, trust, and reflection. Using an automotive climate control system as an example, we show how some of these attributes can be used to evaluate user interactions and point to new design opportunities. Based on results from a pilot study of driver interaction with the climate control system, we operationalized sensitivity and caring for other team members, encapsulated them in a computational architecture, and implemented a control interface. The evaluation of the control interface during a driving experiment suggests that it is markedly better than a regular interface and is almost as good as a human expert who interacts with the climate control system in response to the driver's needs and wants.

Bicentric Diagrams: A Novel Approach to Manage Design Changes of Interdependent Components in Complex Systems

Complex systems can be conceived as a network of interconnected components. Such a network perspective has been used to predict how design changes in one or more components propagate to other components in the system. Despite such advances it remains an important challenge for engineering managers to identify the set of components that could potentially be affected if design changes affect two interdependent components. To address such a design challenge this paper introduces a novel approach, based on bicentric diagrams, to manage design changes of pairs of interdependent components of complex systems. Bicentric diagrams, a novel graph-based visualization technique, enable simultaneous identification of the components that would be directly or indirectly affected if design changes on a pair of interdependent components take place. We illustrate our approach by using bicentric diagrams to examine the impact of changing some critical interfaces of a climate control system and a large commercial aircraft engine.

Real-Time Distributed Economic Model Predictive Control for Complete Vehicle Energy Management

In this paper, a real-time distributed economic model predictive control approach for complete vehicle energy management (CVEM) is presented using a receding control horizon in combination with a dual decomposition. The dual decomposition allows the CVEM optimization problem to be solved by solving several smaller optimization problems. The receding horizon control problem is formulated with variable sample intervals, allowing for large prediction horizons with only a limited number of decision variables and constraints in the optimization problem. Furthermore, a novel on/off control concept for the control of the refrigerated semi-trailer, the air supply system and the climate control system is introduced. Simulation results on a low-fidelity vehicle model show that close to optimal fuel reduction performance can be achieved. The fuel reduction for the on/off controlled subsystems strongly depends on the number of switches allowed. By allowing up to 15-times more switches, a fuel reduction of 1.3% can be achieved. The approach is also validated on a high-fidelity vehicle model, for which the road slope is predicted by an e-horizon sensor, leading to a prediction of the propulsion power and engine speed. The prediction algorithm is demonstrated with measured ADASIS information on a public road around Eindhoven, which shows that accurate prediction of the propulsion power and engine speed is feasible when the vehicle follows the most probable path. A fuel reduction of up to 0.63% is achieved for the high-fidelity vehicle model.

United Technologies Corporation: Running a Global Ethics and Compliance Program

Overview of ethics and compliance program within a multinational corporation; outlines some of the challenges faced with integrating a newly acquired business. Excerpt UVA-BRI-1001 United Technologies Corporation: RUNNING a GLOBAL Ethics and COMPLIANCE Program In July 2003, Pat Gnazzo, Vice President of Business Practices for United Technologies Corporation (UTC), sat at his desk in the company's Hartford, Connecticut, headquarters considering the challenge of integrating 46,000 new employees into UTC's global ethics and compliance program from the recently acquired Chubb plc, a United Kingdom-based leader in security and fire protection services. Although Gnazzo had faced many difficult issues since he had taken over business practices programs for UTC in 1995, this challenge was unique. Simultaneously integrating this volume of employees—who were situated in a variety of different cultures across the globe—would be a monumental task, especially since Chubb's ethics and compliance priorities were not on the level of UTC's. Gnazzo wondered where he should start. History of UTC and Business Units United Technologies Corporation was a $ 31 billion global corporation made up of seven business units and a stand-alone research center, which supported research for all divisions. The business unit divisions were Carrier Corporation (climate control systems), Hamilton Sundstrand (airplane systems), Otis Elevator, Pratt & Whitney (airplane engines), Sikorsky (helicopters), UTC Power (hydrogen fuel cells), and the recently acquired Chubb (security and fire protection services). A global conglomerate with 205,700 employees after the Chubb acquisition (138,000 based outside of the United States), UTC had over 4,000 locations in approximately 62 countries and did business in more than 180 countries. In 2002, 55% of UTC's total revenues came from outside the United States, and its net income was $ 2.2 billion with assets totaling $ 29.1 billion. In March 2003, UTC ranked 49th on the Fortune 500 list of companies. . . .

STRUCTURE OF DECISION SUPPORT SYSTEM OF INFORMATION SYSTEM INTELLIGENT CLIMATE CONTROL RESIDENTIAL

Context. The ever-growing tendency to rise in price of energy makes it necessary to reduce power consumption, that is, to save energy.In terms of accommodation, the introduction of microclimate necessary for the organization of comfortable conditions for the subjects andeconomical use of energy.Objective. The purpose of work is to solve the actual problem of energy-efficient indoor climate control based on the use of informationintellectual system which takes into account the wishes of the subjects are there, which in turn, helps to ensure effective management ofheating devices by reducing or increasing the ambient temperature.Method. The solution of the problem suggested by the use of expert system structure as a component of the intelligent control system ofindoor climate through the use of neuro-fuzzy inference subsystem. This subsystem allows you to automatically generate control informationfor indoor climate control, depending on the wishes of the subjects, summarizing information on the time and place of their stay in differentperiods of time. As a logical subsystem suggested a five-layer neuro-fuzzy feedforward error system, which implements the fuzzy inferenceSugeno zero order. Scheme of intelligent indoor climate control system is also proposed and the approach to the implementation of the processof identifying the subjects in the room.Results. The experimental results confirmed the efficiency of the proposed expert system structure in systems «Smart House». It was also set parameters affecting the quality and performance of the proposed system. As an energy source, natural gas has been elected, and the average temperature ranges premises.Conclusions. A feature of the proposed system is the versatility of the use of any air conditioning, as well as to automatically adjust theroom climate to meet the wishes of subjects. Also, the main feature of the proposed method is to determine the microclimate settings andmemory behavior of the subjects of the room combined with neural networks makes it possible to predict and detect relevant indoor climatevalues, and as a result, to save energy.

Reinforcement learning-based thermal comfort control for vehicle cabins

Vehicle climate control systems aim to keep passengers thermally comfortable. However, current systems control temperature rather than thermal comfort and tend to be energy hungry, which is of particular concern when considering electric vehicles. This paper poses energy-efficient vehicle comfort control as a Markov Decision Process, which is then solved numerically using Sarsa(λ) and an empirically validated, single-zone, 1D thermal model of the cabin. The resulting controller was tested in simulation using 200 randomly selected scenarios and found to exceed the performance of bang-bang, proportional, simple fuzzy logic, and commercial controllers with 23%, 43%, 40%, 56% increase, respectively. Compared to the next best performing controller, energy consumption is reduced by 13% while the proportion of time spent thermally comfortable is increased by 23%. These results indicate that this is a viable approach that promises to translate into substantial comfort and energy improvements in the car.

Multi-objective optimization and decision making for greenhouse climate control system considering user preference and data clustering

Optimization of the systems can increase their efficiency with appropriate system performance indices. Nowadays, climate control of industrial greenhouses consists of many control parameters such as light, temperature, CO$$_{2}$$2 concentration, humidity, and etc. Most of these systems use the PID control structure due to its simplicity, flexibility, and good performance. The electrical lamps and heaters can be used to provide appropriate light and temperature inside the greenhouse. Optimal tuning of electrical lamps and heaters control system has a significant influence on efficiency and performance improvement of greenhouse cultivation system. For this aim, NSGA-II, a well-known evolutionary algorithm, is applied for the system optimization verified with an exhaustive search approach. Making a final decision to choose the best solution among the optimal solutions is a challenging decision making issue. In this regard, post Pareto-optimal pruning algorithms are employed considering various user preferences and clustering approaches. The final results show and verify the substantial improvement of greenhouse climate control system efficiency and performance.

Climate-responsive design: A framework for an energy concept design-decision support tool for architects using principles of climate-responsive design

Climate-responsive design: A framework for an energy concept design-decision support tool for architects using principles of climate-responsive design

Greenhouse Climate Control and Monitoring System

Greenhouse Climate Control and Monitoring System

Climate-responsive design: A framework for an energy concept design-decision support tool for architects using principles of climate-responsive design

Climate-responsive design: A framework for an energy concept design-decision support tool for architects using principles of climate-responsive design

Climate-responsive design: A framework for an energy concept design-decision support tool for architects using principles of climate-responsive design

Climate-responsive design: A framework for an energy concept design-decision support tool for architects using principles of climate-responsive design